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- 19Planning
- 12Heuristic Search
- 7Artificial Intelligence
- 6Abstractions
- 6Reinforcement Learning
- 3Machine Learning
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Author / Creator / Contributor
- 1Abdullah
- 1Asadi Atui, Kavosh
- 1Barriga Richards, Nicolas A
- 1Brown, Jennifer A.
- 1Faid, Julian TW
- 1Fan, Gaojian
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Fall 2019
In this thesis, we study merge-and-shrink (M&S), a flexible abstraction technique for generating heuristics for cost optimal planning. We first propose three novel merging strategies for M&S, namely, Undirected Min-Cut (UMC), Maximum Intermediate Abstraction Size Minimizing (MIASM), and Dynamic...
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Spring 2016
Game theoretic solution concepts, such as Nash equilibrium strategies that are optimal against worst case opponents, provide guidance in finding desirable autonomous agent behaviour. In particular, we wish to approximate solutions to complex, dynamic tasks, such as negotiation or bidding in...
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